• Journal of Korea Society of Industrial Information Systems
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• v.24 no.6
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• pp.43-53
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• 2019

In recent years, there have been many cases of damage to indoor air hazardous materials, and major damage due to the lack of quick action. In this regard, the system is intended to establish for sending push messages to the user's mobile when the concentration of hazardous substances is exceeded. This system extracts data with IoT system such as Arduino and Raspberry Pi and then constructs database through MongoDB and MySQL in cloud computing system. The database is imported through the application server using NodeJS and sent to the application for visualization. Also, when receiving signals about a dangerous situation in IoT system, push message is sent using Google FCM library. Mobile application is developed using Android Web view, and page to enter Web view is developed using HTML5 (HTML, Javascript CSS). The application of this system enables real-time monitoring of indoor air-dangerous substances. In addition, real-time information on indoor/outdoor detection location and concentration can be sent to the user's mobile in case of a risk situation, which can be expected to help the user respond quickly.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.301-307
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• 2023

Deep learning requires building a deep neural network, collecting a large amount of training data, and then training the built neural network for a long time. If training does not proceed properly or overfitting occurs, training will fail. When using deep learning tools that have been developed so far, it takes a lot of time to collect training data and learn. However, due to the rapid advent of the mobile environment and the increase in sensor data, the demand for real-time deep learning technology that can dramatically reduce the time required for neural network learning is rapidly increasing. In this study, a real-time deep learning system was implemented using an Arduino system equipped with a fine dust sensor. In the implemented system, fine dust data is measured every 30 seconds, and when up to 120 are accumulated, learning is performed using the previously accumulated data and the newly accumulated data as a dataset. The neural network for learning was composed of one input layer, one hidden layer, and one output. To evaluate the performance of the implemented system, learning time and root mean square error (RMSE) were measured. As a result of the experiment, the average learning error was 0.04053796, and the average learning time of one epoch was about 3,447 seconds.

• Journal of Internet of Things and Convergence
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• v.10 no.4
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• pp.9-19
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• 2024

In this paper, a real-time public transportation monitoring system is proposed. The proposed system was implemented by developing a public transportation app and utilizing optical sensors, pressure sensors, and an object detection algorithm. Additionally, a bus model was created to verify the system's functionality. The proposed real-time public transportation monitoring system has three key features. First, the app can monitor congestion levels within public transportation by detecting seat occupancy and the total number of passengers based on changes in optical and pressure sensor readings. Second, to prevent errors in the optical sensor that can occur when multiple passengers board or disembark simultaneously, we explored the possibility of using the YOLO object detection algorithm to verify the number of passengers through CCTV footage. Third, convenience is enhanced by displaying occupied seats in different colors on a separate screen. The system also allows users to check their current location, available public transportation options, and remaining time until arrival. Therefore, the proposed system is expected to offer greater convenience to public transportation users.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1061-1064
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• 2017

자전거 이용자 수가 천만 명을 넘으면서, 자전거 사업은 우리의 삶에 중요 요소로 자리 잡게 되었다. 본 연구에서는 자전거 사용자들에게 편의를 제공하기 위해 GPS정보를 기반으로 한 자전거 전용 네비게이션과 사용자들을 자전거 사고로부터 보호할 수 있는 사고 대처 시스템을 개발하였다. 이를 위해 우리는 아두이노기반의 시스템을 토대로 개발되었으며 스마트폰과 블루투스 송신기술을 사용하여 다양한 정보를 주고 받을 수 있도록 설계하였다. 우리의 사고 대처시스템은 실시간으로 자전거 운행 정보를 공유하도록 하여 보다 효율적으로 자전거 사고를 예방 할 수 있도록 하는데 그 목적이 있다. 이를 위해 우리의 시스템은 아두이노를 통해 측정한 센서 값들을 스마트폰을 통해 자전거 사용자들에게 실시간으로 공유되도록 하고 이를 통해 다른 자전거 사용자들이 자전거 도로의 상태, 사고 내용들을 파악하도록 하여 안전하고 편리한 자전거 운행이 가능하도록 하여 향후 자전거 사업이 발전시킬 수 있는 계기를 마련할 것으로 기대한다.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.6
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• pp.867-874
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• 2021

The IoT (Internet of Things) technology is rapidly becoming an important consideration in many engineering fields in the current 4th industrial era. In recent years, the concepts of digital shipbuilding and smart factories have been adopted as trends in shipyards. However, there is active interest in research on implementing autonomous driving in autonomous vehicles and airplanes, which is currently available in commercial form in a limited capacity. The present study is regarding the path-tracking performance of a boat to accomplish an autonomous driving mission using a flight controller (FC) and real-time kinematic (RTK) global positioning system (GPS) based on an open-source Ardupilot; an actual sea test is also performed using this system on a calm lake. The boat's mission is to evaluate the maneuverability of the self-driving process to a specific point and returning to the home position. For a given speed, the difference between the preset mission trajectory and actual operational trajectory was analyzed, and a series of studies were conducted on the applicability of the system to ships. In addition, the movements and maneuverability of the OmniX-type hull with four propellers were investigated, and the driving path-tracking performance was observed to increase by a maximum of 48%.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.4
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• pp.421-426
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• 2016

Fluid is normally used so that certain drug can be administered to patients for certain period of time. There are many incidents in which patients or guardians need to call upon medical staff after estimating the time of fluid injection termination. In case fluid injection is terminated during certain period such as sleeping time or others, it may cause more fatigue for either patients or guardians. Also, it may lead to ineffective work as medical staff needs to monitor the quantity of fluid several times in order to check the time of fluid injection termination. Therefore, the purpose of this study is to propose LBS system combined of minimum equipment and active RFID to monitor the level of fluid in order to solve abovementioned problems. Also, it is expected to enhance the quality of medical service with service in which real-time monitoring of fluid quantity and patient location is conducted to provide accurate information to either patients, guardians, or medical staff(nurse) so that medical staff can locate and see patients at the time of fluid injection termination.

• The Journal of Korean Association of Computer Education
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• v.19 no.6
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• pp.45-54
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• 2016

The purpose of this study is to investigate the effects of Android application programming education to control Arduino using App Inventor on industrial high school students' creative and integrative thinking ability. We developed an instructional content based on integrative learning and creative problem-solving model and taught a class on it. The result of this study showed that there was a significant improvement in divergent thinking and motivation items among the sub elements of creative problem solving. In addition, students' survey on the integrated thinking has shown that many students think that they could design an IoT system applied to everyday life based on the knowledge they have learned in this class. Therefore, it can be confirmed that physical computing education using App Inventor and Arduino has a positive effect on students' creative and integrative thinking ability.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.924-926
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• 2015

In this paper, we use the interface, which many countries concentrates research of Brain - Computer Interface with the device and MyndPlay based on the IoT intelligent Arduino. Finally we will make the Brain - Computer Connection environment, the purpose of Brain - Computer Interface. Recognizes the EEG of a person who wearing the equipment, analyze, classify, and we did a research to design an intelligent thing to suit user's condition. In addition, we use the XBee, and Bluetooth to communicate to other devices, such as smart phone. In conclusion, this paper check users current status via brain waves, and it allows to control the power and other objects by using the EEG(Electroencephalography).

• Journal of Convergence for Information Technology
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• v.7 no.4
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• pp.91-96
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• 2017

In this paper, we aim to respond efficiently to crime by using Arduino and smartphone apps in response to increasing number of house-breaking crimes. It receives the signal of the sensor installed in the house and connects it with the app of the smartphone. To use the app, you can download the app from the user's smartphone, launch the app, and operate the operation outside the home, not only inside the house, by linking the executed app. Among the sensors installed in the house, the movement detection sensor is used to enhance the security, and the gas leakage sensor and the flame detection sensor can be used to easily detect the risk of fire and to prevent the fire early. Security is further enhanced by the ability to remotely control the front door with a smartphone. After that, various sensors can be added and it can be developed as a WiFi module in addition to the Bluetooth module.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1132-1140
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• 2016

According to global trend, despite the overall scale of agricultural industry has been downsized, agriculture accommodating cutting-edge ICT technologies has been proliferated, and various timely-issued relevant researches have been on progress to deploy the future food cultivation. In this paper, we propose an effective nutrient management system with web-based monitoring with functionality of controlling temperature, humidity, pH (hydrogen ion), EC (Electric Conductivity), LED and cooling fan to maintain the hydroponic nurturing environment being optimal. In this paper, in order the arduino hardware and java software are employed to control the nurturing environment automatically in optimal fashion. In proposed system, due to the usage of WiFi router with the socket communication and DB-assisted Web server with proper interfaces, it allows to facilitate the management to keep monitoring and controling overall hydroponic nurturing environment. Since the proposed Web-based management system provides the superior reliability, the short nurturing period and the robustness to the pest by controlling LED emitting color rather than conventional system, so it can be applied and appropriate for in-house vegetable factory overcoming limitation of time and location.